{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# pandas中数据选取操作"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>age</th>\n",
       "      <th>height</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>张三</td>\n",
       "      <td>18</td>\n",
       "      <td>1.68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>李四</td>\n",
       "      <td>19</td>\n",
       "      <td>1.73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>王五</td>\n",
       "      <td>17</td>\n",
       "      <td>1.62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>赵六</td>\n",
       "      <td>20</td>\n",
       "      <td>1.55</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  name  age  height\n",
       "0   张三   18    1.68\n",
       "1   李四   19    1.73\n",
       "2   王五   17    1.62\n",
       "3   赵六   20    1.55"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = {\n",
    "    'name':['张三','李四','王五','赵六'],\n",
    "    'age':[18,19,17,20],\n",
    "    'height':[1.68,1.73,1.62,1.55]\n",
    "}\n",
    "df = pd.DataFrame(data,columns=['name','age','height'])\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    张三\n",
       "1    李四\n",
       "2    王五\n",
       "3    赵六\n",
       "Name: name, dtype: object"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['name']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    18\n",
       "1    19\n",
       "2    17\n",
       "3    20\n",
       "Name: age, dtype: int64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.age"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>张三</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>李四</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>王五</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>赵六</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  name\n",
       "0   张三\n",
       "1   李四\n",
       "2   王五\n",
       "3   赵六"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[['name']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    张三\n",
       "1    李四\n",
       "2    王五\n",
       "3    赵六\n",
       "Name: name, dtype: object"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "names = df['name']\n",
    "names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\users\\jack-pc\\appdata\\local\\programs\\python\\python37-32\\lib\\site-packages\\ipykernel_launcher.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  \"\"\"Entry point for launching an IPython kernel.\n"
     ]
    }
   ],
   "source": [
    "names[0] = 'lili'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    lili\n",
       "1      李四\n",
       "2      王五\n",
       "3      赵六\n",
       "Name: name, dtype: object"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <td>1.68</td>\n",
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       "      <th>1</th>\n",
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       "      <td>1.73</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>王五</td>\n",
       "      <td>17</td>\n",
       "      <td>1.62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>赵六</td>\n",
       "      <td>20</td>\n",
       "      <td>1.55</td>\n",
       "    </tr>\n",
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       "</table>\n",
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      ],
      "text/plain": [
       "   name  age  height\n",
       "0  lili   18    1.68\n",
       "1    李四   19    1.73\n",
       "2    王五   17    1.62\n",
       "3    赵六   20    1.55"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['name', 'age', 'height'], dtype='object')"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['age', 'height'], dtype='object')"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns[1:3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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      "text/plain": [
       "   age  height\n",
       "0   18    1.68\n",
       "1   19    1.73\n",
       "2   17    1.62\n",
       "3   20    1.55"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "df[df.columns[1:3]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "import datetime"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>age</th>\n",
       "      <th>height</th>\n",
       "      <th>year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>lili</td>\n",
       "      <td>18</td>\n",
       "      <td>1.68</td>\n",
       "      <td>2000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>李四</td>\n",
       "      <td>19</td>\n",
       "      <td>1.73</td>\n",
       "      <td>1999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>王五</td>\n",
       "      <td>17</td>\n",
       "      <td>1.62</td>\n",
       "      <td>2001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>赵六</td>\n",
       "      <td>20</td>\n",
       "      <td>1.55</td>\n",
       "      <td>1998</td>\n",
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      ],
      "text/plain": [
       "   name  age  height  year\n",
       "0  lili   18    1.68  2000\n",
       "1    李四   19    1.73  1999\n",
       "2    王五   17    1.62  2001\n",
       "3    赵六   20    1.55  1998"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['year'] = datetime.datetime.now().year - df.age\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>1.68</td>\n",
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       "      <td>李四</td>\n",
       "      <td>19</td>\n",
       "      <td>1.73</td>\n",
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       "      <th>2</th>\n",
       "      <td>王五</td>\n",
       "      <td>17</td>\n",
       "      <td>1.62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>赵六</td>\n",
       "      <td>20</td>\n",
       "      <td>1.55</td>\n",
       "    </tr>\n",
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      ],
      "text/plain": [
       "   name  age  height\n",
       "0  lili   18    1.68\n",
       "1    李四   19    1.73\n",
       "2    王五   17    1.62\n",
       "3    赵六   20    1.55"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.drop('year',axis = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <td>1.73</td>\n",
       "      <td>1999</td>\n",
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       "      <td>1.62</td>\n",
       "      <td>2001</td>\n",
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       "      <th>3</th>\n",
       "      <td>赵六</td>\n",
       "      <td>1.55</td>\n",
       "      <td>1998</td>\n",
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      ],
      "text/plain": [
       "   name  height  year\n",
       "0  lili    1.68  2000\n",
       "1    李四    1.73  1999\n",
       "2    王五    1.62  2001\n",
       "3    赵六    1.55  1998"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.drop(df.columns[1:2],axis = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "name        李四\n",
       "age         19\n",
       "height    1.73\n",
       "year      1999\n",
       "Name: 1, dtype: object"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
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       "   name  age  height  year\n",
       "0  lili   18    1.68  2000\n",
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       "2    王五   17    1.62  2001\n",
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       "4  jack   21    1.66  2000\n",
       "5  jack   21    1.66  2000"
      ]
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   "source": [
    "df.loc[df.shape[0]] = {'age':21,'name':'jack','height':1.66,'year':2000}\n",
    "df"
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       "   name  age  height  year\n",
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       "   name  age  height  year\n",
       "0  lili   18    1.68  2000\n",
       "1    李四   19    1.73  1999\n",
       "2    王五   17    1.62  2001\n",
       "3    赵六   20    1.55  1998\n",
       "5  jack   21    1.66  2000"
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   "source": [
    "df2 = df.drop(4)\n",
    "df2"
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   "execution_count": 50,
   "metadata": {},
   "outputs": [
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      "text/plain": [
       "   name  age  height  year\n",
       "0  lili   18    1.68  2000\n",
       "1    李四   19    1.73  1999\n",
       "2    王五   17    1.62  2001\n",
       "3    赵六   20    1.55  1998\n",
       "4  jack   21    1.66  2000"
      ]
     },
     "execution_count": 50,
     "metadata": {},
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   "source": [
    "df2.index = range(df2.shape[0])\n",
    "df2"
   ]
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   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
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       "      <th>B</th>\n",
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       "      <td>19</td>\n",
       "      <td>1.73</td>\n",
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       "      <td>2001</td>\n",
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       "    <tr>\n",
       "      <th>D</th>\n",
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       "    <tr>\n",
       "      <th>E</th>\n",
       "      <td>jack</td>\n",
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       "   name  age  height  year\n",
       "A  lili   18    1.68  2000\n",
       "B    李四   19    1.73  1999\n",
       "C    王五   17    1.62  2001\n",
       "D    赵六   20    1.55  1998\n",
       "E  jack   21    1.66  2000"
      ]
     },
     "execution_count": 53,
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    "df2.index = list(\"ABCDE\")\n",
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       "  name  age  height  year\n",
       "B   李四   19    1.73  1999\n",
       "C   王五   17    1.62  2001"
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       "19"
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       "   name  age  height  year\n",
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   "execution_count": 60,
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   "outputs": [
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       "2    王五   17    1.62  2001\n",
       "3    赵六   20    1.55  1998"
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       "   name  age  height  year\n",
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   "execution_count": 62,
   "metadata": {},
   "outputs": [
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       "  name  age  height  year\n",
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   "source": [
    "age = 20\n",
    "df.query('age == @age')"
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   "execution_count": 63,
   "metadata": {},
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   "execution_count": 64,
   "metadata": {},
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